Triple

T13004717
Position Surface form Disambiguated ID Type / Status
Subject Elton Tiscia E322254 entity
Predicate basedOnWork P7125 FINISHED
Object Emma
Emma is a classic 1815 novel by Jane Austen that follows the romantic misadventures and personal growth of a clever but meddlesome young woman in an English village.
 E326305 NE FINISHED

How this triple was built (4 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Emma | Statement: [Elton Tiscia, basedOnWork, Emma]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Emma
Context triple: [Elton Tiscia, basedOnWork, Emma]
  • A. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • B. Emma
    "Emma" is a 2009 British television miniseries adaptation of Jane Austen's novel, starring Romola Garai in the title role.
  • C. Emma
    Emma is a central character in Sam Shepard’s play "Curse of the Starving Class," portrayed as a rebellious and sharp-witted teenage girl struggling against her dysfunctional family and bleak circumstances.
  • D. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • E. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Emma
Triple: [Elton Tiscia, basedOnWork, Emma]
Generated description
Emma is a classic 1815 novel by Jane Austen that follows the romantic misadventures and personal growth of a clever but meddlesome young woman in an English village.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Emma
Target entity description: Emma is a classic 1815 novel by Jane Austen that follows the romantic misadventures and personal growth of a clever but meddlesome young woman in an English village.
  • A. Emma
    Emma is a common feminine given name of Germanic origin, widely used in English-speaking and many other countries.
  • B. Emma chosen
    "Emma" is a 2009 British television miniseries adaptation of Jane Austen's novel, starring Romola Garai in the title role.
  • C. Emma
    Emma is a central character in Sam Shepard’s play "Curse of the Starving Class," portrayed as a rebellious and sharp-witted teenage girl struggling against her dysfunctional family and bleak circumstances.
  • D. Emily
    Emily Warren Roebling was a pioneering 19th-century American engineer best known for her crucial role in overseeing the completion of the Brooklyn Bridge.
  • E. Emily
    Emily is a given name commonly used in English-speaking countries, often associated with literary, historical, and contemporary cultural figures.
  • F. None of above.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e9a2a448190968833354280e474 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5f4bedc81909b8dfa79a842e12d completed May 3, 2026, 4:58 a.m.
NEDg Description generation batch_69f6da5695508190a96ca16a4e5c01ee completed May 3, 2026, 5:17 a.m.
NED2 Entity disambiguation (via description) batch_69f6daeae96081908f6d9cda3ff7f961 completed May 3, 2026, 5:19 a.m.
Created at: April 9, 2026, 8:47 p.m.